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20162022
most citedProbabilistic Forecasting of Sensory Data with Generative Adversarial Networks - ForGAN

95 citations · 339 across the 39 of their papers we have counts for

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7 papers · 1 filter

cs.AI20222 cited

Improving Health Mentioning Classification of Tweets using Contrastive Adversarial Training

Pervaiz Iqbal Khan, Shoaib Ahmed Siddiqui, Imran Razzak +2

Health mentioning classification (HMC) classifies an input text as health mention or not. Figurative and non-health mention of disease words makes the classification task challengi…

cs.AI20221 cited

Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods

Dominique Mercier, Jwalin Bhatt, Andreas Dengel +1

In the last decade neural network have made huge impact both in industry and research due to their ability to extract meaningful features from imprecise or complex data, and by ach…

cs.AI2022

ExAID: A Multimodal Explanation Framework for Computer-Aided Diagnosis of Skin Lesions

Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun +3

One principal impediment in the successful deployment of AI-based Computer-Aided Diagnosis (CAD) systems in clinical workflows is their lack of transparent decision making. Althoug…

cs.AI2021

XAI Handbook: Towards a Unified Framework for Explainable AI

Sebastian Palacio, Adriano Lucieri, Mohsin Munir +3

The field of explainable AI (XAI) has quickly become a thriving and prolific community. However, a silent, recurrent and acknowledged issue in this area is the lack of consensus re…

cs.AI20207 cited

Achievements and Challenges in Explaining Deep Learning based Computer-Aided Diagnosis Systems

Adriano Lucieri, Muhammad Naseer Bajwa, Andreas Dengel +1

Remarkable success of modern image-based AI methods and the resulting interest in their applications in critical decision-making processes has led to a surge in efforts to make suc…

cs.AI2020

P2ExNet: Patch-based Prototype Explanation Network

Dominique Mercier, Andreas Dengel, Sheraz Ahmed

Deep learning methods have shown great success in several domains as they process a large amount of data efficiently, capable of solving complex classification, forecast, segmentat…